Use the given code below to answer the questions.

Q1 Import Netflix stock prices, instead of Apple.

Hint: Insert a new code chunk below and type in the code, using the tq_get() function above. Replace the ticker symbol. Find ticker symbols from Yahoo Finance.

## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis

## Import data
stocks <- tq_get("NFLX", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 1,033 x 7
##    date        open  high   low close   volume adjusted
##    <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
##  1 2016-01-04  109   110   105.  110. 20794800     110.
##  2 2016-01-05  110.  111.  106.  108. 17664600     108.
##  3 2016-01-06  105.  118.  105.  118. 33045700     118.
##  4 2016-01-07  116.  122.  112.  115. 33636700     115.
##  5 2016-01-08  116.  118.  111.  111. 18067100     111.
##  6 2016-01-11  112.  117.  111.  115. 21920400     115.
##  7 2016-01-12  116.  118.  115.  117. 15133500     117.
##  8 2016-01-13  114.  114.  105.  107. 24921600     107.
##  9 2016-01-14  106.  109.  101.  107. 23664800     107.
## 10 2016-01-15  102.  106.  102.  104. 19775100     104.
## # … with 1,023 more rows

Q2 How many shares of the stock were traded on January 13, 2017?

10515000 shares of the stock were traded on January 13, 2017 by Netflix.

Q3 Stock prices in this data would be a good example of numeric data. Character and logical are two other basic data types in R. List one example of character data and one example of logical data.

Hint: Watch the video, “Basic Data Types”, in DataCamp: Introduction to R for Finance: Ch1 The Basics. An example of logical data would be the TRUE or FALSE values and an example 0f character data is numbers letters and symbols.

Q4 Plot the closing price in a line chart.

Hint: Insert a new code chunk below and type in the code, using the ggplot() function above. Revise the code so that it maps close to the y-axis, instead of adjusted.

## Visualize
stocks %>%
  ggplot(aes(x = date, y = close)) +
  geom_line()

``` ## Q5 From the chart you created in Q4, briefly describe how the Netflix stock has performed since the beginning of 2019. Since the beginning of 2019, the Netflix stock has performed pretty well. In the first few months of 2019, Netflix was booming. As we get into the middle months, we see Netflix start to make a pretty steady drop off close to where they started the year. However Netflix starts going back up in the later 2019 years and is doing quite well in the first two months of 2020.

Q6 Import two stocks: Netflix and Amazon for the same time period.

Hint: Insert a new code chunk below and type in the code, using the tq_get() function above. You may refer to the manual of the tidyquant r package. Or, simply Google the tq_get function and see examples of the function’s usage.

## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis

## Import data
stocks <- tq_get("AMZN", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 1,033 x 7
##    date        open  high   low close  volume adjusted
##    <date>     <dbl> <dbl> <dbl> <dbl>   <dbl>    <dbl>
##  1 2016-01-04  656.  658.  628.  637. 9314500     637.
##  2 2016-01-05  647.  647.  628.  634. 5822600     634.
##  3 2016-01-06  622   640.  620.  633. 5329200     633.
##  4 2016-01-07  622.  630   605.  608. 7074900     608.
##  5 2016-01-08  620.  624.  606   607. 5512900     607.
##  6 2016-01-11  612.  620.  599.  618. 4891600     618.
##  7 2016-01-12  625.  626.  612.  618. 4724100     618.
##  8 2016-01-13  621.  621.  579.  582. 7655200     582.
##  9 2016-01-14  580.  602.  570.  593  7238000     593 
## 10 2016-01-15  572.  585.  565.  570. 7784500     570.
## # … with 1,023 more rows
## Import data
stocks <- tq_get("NFLX", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 1,033 x 7
##    date        open  high   low close   volume adjusted
##    <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
##  1 2016-01-04  109   110   105.  110. 20794800     110.
##  2 2016-01-05  110.  111.  106.  108. 17664600     108.
##  3 2016-01-06  105.  118.  105.  118. 33045700     118.
##  4 2016-01-07  116.  122.  112.  115. 33636700     115.
##  5 2016-01-08  116.  118.  111.  111. 18067100     111.
##  6 2016-01-11  112.  117.  111.  115. 21920400     115.
##  7 2016-01-12  116.  118.  115.  117. 15133500     117.
##  8 2016-01-13  114.  114.  105.  107. 24921600     107.
##  9 2016-01-14  106.  109.  101.  107. 23664800     107.
## 10 2016-01-15  102.  106.  102.  104. 19775100     104.
## # … with 1,023 more rows

Q7 Hide the messages and the results of the code, but display the code on the webpage.

Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.

Q8 Make an exception to the code chunk in Q6 by displaying both the code and its results.

Hint: Use echo and results in the chunk option. Note that this question only applies to the individual code chunk of Q6.

Q9 Display the title and your name correctly at the top of the webpage.

Q10 Use the correct slug.